journal article·2014-10

A facile one-pot synthesis of gadolinium doped TiO2-based nanosheets with efficient visible light-driven photocatalytic performance

Dingze Lu, Pengfei Fang, Yang Liu, Zhi Liu, Xinzhao Liu, Yuanpeng Gao, Feitai Chen, Fei Niu

Journal of Nanoparticle Research· Volume 16· Issue 10
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Abstract

Gadolinium doped TiO2-based nanosheets (Gd-TNSs) with different Gd/Ti ratios are prepared by a facile one-pot hydrothermal method using gadolinium nitrate as the gadolinium precursor. The photocatalysts are characterized by high-resolution transmission electron microscopy (HRTEM), Raman spectra, X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), ultraviolet–visible light diffuse reflectance spectra (DRS), fluorescence spectra (FL), and N2 adsorption–desorption measurement. The as-synthesized samples show clearly sheet-like structure, with the width of about 30–100 nm, length greater than 100 nm, and high specific surface area (200–300 m2/g). The patterns of XRD and Raman analyses indicate that doped gadolinium has obvious influence on the structure of samples. The band-gap energy (E g) of photocatalysts reduce from 3.17 to 3.02 eV with the content of gadolinium increasing from 0.1 to 1.5 at. %. The FL emission intensity initially decreases with the content of Gd increasing and then increases after minimizing at 0.5 %-Gd-TNSs, which reveals that appropriate amount of gadolinium doping can effectively inhibit the recombination of photo-generated electrons and holes. The adsorption capacity and photocatalytic activity are evaluated by Rhodamine B (RhB). The best photocatalytic performance is obtained when the doping ratio of gadolinium is 0.5 at. %. The visible reaction rate (K app) of 0.5 %-Gd-TNSs was 2.0-fold as compared to TNSs, and 4.7-fold as compared to P25. The possible mechanisms for enhanced visible-light photocatalytic activities are discussed in detail.
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Research context

OpenAlex topics: Advanced Photocatalysis Techniques · TiO2 Photocatalysis and Solar Cells · Catalytic Processes in Materials Science

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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